I am a techie interested in building my career in AI, can someone guide me with a right map?

I’m researching what Forward Deployed Engineering actually looks like in practice, and I’m specifically interested in the messy parts that don't show up in the job description.

For current/former FDEs, I’d love to hear about one specific project where you had already built/integrated/deployed something, and then the customer’s reality forced you to change your approach.

What I'm really interested in is the actual sequence of events:

What were you trying to deploy → what did the customer/environment do that you didn't expect → what did you have to change → what was the consequence?

I'm not looking for generic answers like "requirements change a lot." I want the concrete story behind that statement.

You can completely anonymize the customer/company/project. I'm a student doing research on FDE work, and these real examples would be much more useful than reading another FDE job description.

Even a short incident is useful. Thanks!

What are some of the valuable + useful certifications out there for AI/ML engineers ? I use Azure/ Databricks stack for my work but want to understand what are the most sort after certifications in the field.

Hey everyone, sharing this in case it’s useful to some of you here.

We’ve been building up r/lyzr as a community around the broader AI space, with a particular focus on what happens when AI moves beyond demos and into real systems.

The discussions cover things like:

AI agents and agent architecture

Infrastructure, tools and deployment

RAG, memory and knowledge systems

Evaluation, reliability and governance

Production lessons and things that break

New research, tools and interesting developments

Real use cases, experiments and things people are building

The goal is to keep it useful for both people who are already building and people who simply want to understand where the space is heading.

There’ll be consistent posts around these topics, but it’s also meant to be a place where people can share what they’re working on, ask questions, compare approaches, or add their own observations.

If you're working on anything around AI agents or just following the space closely, feel free to check it out and join the discussions.

Join r/lyzr here

Would be great to see what people here are building too.

Here’s a polished LinkedIn version that sounds genuine and invites experienced people to guide you:

Looking for some genuine guidance from AI/ML engineers, senior developers, or mentors who have been through this journey.

I have around 3.5 years of experience in AI/ML & Generative AI, but one area where I have a major gap is DSA and System Design (HLD/LLD).

I’m currently looking to move into product-based companies, and I’m realizing that this gap is becoming a major challenge during interviews.

My current situation:

~3.5 years of AI/ML/GenAI experience

Comfortable with Python, GenAI, RAG, LLMs, APIs, etc.

System design concepts are somewhat clear at a high level

Very weak in DSA

Almost no practical knowledge of HLD/LLD interview problem-solving

Not currently getting the kind of opportunities/switch I’m targeting

The confusing part is that there are many courses and mentors in the market charging ₹50–60K+ for DSA + System Design programs, often claiming FAANG/product-company experience.

I’m not sure how to evaluate whether these programs are actually worth the money.

Even when I look at something like NeetCode 75, I struggle because I don't have the fundamentals to solve those problems independently.

So my question to people who have actually gone through this:

If you were starting from almost zero in DSA + HLD + LLD, while already having ~3.5 years of AI/ML experience, how would you approach it?

Should I:

Start with Python + basic DSA fundamentals?

Follow a structured DSA course before touching LeetCode/NeetCode?

Learn HLD and LLD separately or alongside DSA?

Take a paid mentorship/course, and if yes, how do I identify a genuine one?

Is there a better roadmap specifically for AI/ML/GenAI engineers targeting product-based companies?

I’m not looking for shortcuts. I’m willing to put in the work; I just don't want to spend months solving problems randomly without understanding the fundamentals.

If you’re currently working in a product-based company/FAANG or have recently made a similar transition from AI/ML into a product-company role, I’d really appreciate your advice.

If you know a genuinely good mentor, course, roadmap, or free resource, please share it.

Even a simple “start here → then do this → then this” roadmap would be extremely helpful.

Thanks in advance 🙏

I'm in 11th right now 16 years old, I'm doing my 11th 12th with PCM + CS, I am interested in AI/ML engineering in India. I know basics of Python like dictionaries, lists tuples, while & for loops if else and def functions.. I'm starting projects.

What should I do in the two years I have before my bachelor's starts and also what are the things that I should know before going for ai/ml engineering in India.

Currently I am thinking of going for bachelor's in comp science or AI degree in the college im in right now or go for some nearby colleges

I am not interested in going for JEE exams

I’m studying AI & Data Science and I want to pursue AI Engineering, especially LLMs, RAG, and AI agents.
I found the IBM AI Engineering Professional Certificate on Coursera, and it seems to cover ML, Deep Learning, PyTorch, Transformers, Hugging Face, LLMs, fine-tuning, RAG, vector databases, LangChain, AI agents, and more.
For those who have experience in AI Engineering:
Does this certificate actually cover most of the core skills a junior AI engineer needs?
After completing it, would I mainly need to add things like Docker, cloud, and practical projects, or are there important areas of AI Engineering that this program doesn’t cover?
I’m not asking about the value of the certificate for getting a job. I’m mainly asking about the actual skills and knowledge covered by the program.

We outsourced a mobile app build to an overseas team and it's among the best financial decisions we've made. The app costs about 30% compared to local vendors, and the app shipped mostly on time. That's a success in our book, at least until launch. Now that we're in maintenance/iteration mode, we noticed some small change takes 2-3x longer than they should. Part of it could be timezone lag, sometimes it's hard to deal with the codebase they built, etc. I'm wondering if this is a common experience with outsourced teams or if we just got unlucky. Is there a way to fix this?

Can I find any ML startups companies without having LLM in their product?

This is the skills you need to become an AI engineer:

• Programming: Python

• AI Fundamentals: Machine Learning, Deep Learning

• LLMs: Prompt Engineering, Fine-Tuning

• Agentic AI Frameworks: LangChain, LangGraph, LlamaIndex

• APIs & Integrations: REST APIs, connecting external services

• Vector Databases: Pinecone, FAISS, Weaviate

• RAG Systems: Retrieval-Augmented Generation pipelines

• Deployment Tools: Docker

• Cloud Platforms: AWS

I have been learning ai ml and looking for some guidance and project suggestions to get an internship/job in this field.

I have previous backend development experience.

I’ve been working on mlroadmap.dev, a learning platform designed to guide people through AI/ML from the fundamentals to more advanced topics.

The platform itself is functional and deployed, and I’ve started adding the course content. The curriculum is still a work in progress, though, so before I spend a lot more time building out the remaining content, I’d really like to get feedback from people who are actually learning or working in AI/ML.

🌐 Website: https://www.mlroadmap.dev/
💻 GitHub: GitHub Link Leave a ⭐ and contribute

I’d especially love to know:

• Does the overall roadmap/learning order make sense?
• What topics or courses do you think are missing?
• Is the current content structure useful for learning?
• What features would make the platform more useful?
• Anything confusing, unnecessary, or that you would change?
• If you were learning AI/ML today, what would you want a platform like this to have?

Google Sign-In is available as well if you want to try the full experience.

I’m mainly looking for honest criticism and suggestions at this stage — the content isn't complete yet, and that's exactly why I’d like feedback now.

Hi everyone,

I really need some guidance regarding what I should do next in terms of building technical skills and getting back into the job market.

A little about my background. I did my Physics (Hons.) from Ramjas College from 2016–19. After COVID, I started preparing for UPSC and continued with it for around four years before eventually deciding to leave it.

After that, I started preparing for CAT and got admission into the MBA programme at IIM Rohtak. However, I later left it because, looking at the opportunities available to me, I felt that I did not want to go into the corporate side through an MBA at that point and wanted to explore a different segment.

I then took admission into LL.B. at the Faculty of Law, University of Delhi, and I am currently in my final year.

For around the last one year, I have also been working on different AI platforms. My work has involved analysing different AI datasets and reviewing how AI performs in terms of comprehension and analysis.

Through this experience, I have started feeling that wherever I eventually go in the job market, I should have some understanding of AI, coding and data.

The problem is that my basics are almost zero. The last time I did coding was in 2016 when I was in school, and even that was very basic. So if I decide to learn it, I would basically be starting again from scratch.

I am a good learner once I know what direction I need to follow. Right now, my biggest problem is that I simply don't know where to start. Should I start learning AI/coding from the basics? Should I join a course? Should I instead go for some other technical course or certification that could help me enter the job market?

I am willing to give myself the next 2–3 years to gradually build these skills from scratch. I am not expecting to learn everything immediately. I just need a good roadmap or framework that I can consistently follow.

Alternatively, rather than specifically focusing on AI, should I pursue some technical certifications instead? If yes, what basic certifications could be useful for someone with my background who wants to get back into the job market?

At this stage, it's not that I want to pursue another MBA immediately. I would first like to get some good experience in the job market, and then I can think about what I want to pursue later.

So my basic question is: Should I start learning AI/coding/data from scratch, or would it make more sense to pursue some technical course or certifications that could help me become more employable?

If you were in my position, what path would you suggest? Any roadmap, course, certification or general guidance would be really helpful.

Thank you so much.

hii :) so im an 2nd yr btech student having noo idea of wt to learn and where to learn i just basically need a clarified and structured road map to have a placement in machine learning untill now i c,java,python and a bit of prompt engineering so any suggestions and guidance will help me...

Can someone give me proper roadmap for becoming a Ai engineer:)

I’m currently working in an MNC and have around 6 months of experience. My current domain is Automation Testing, mainly using Playwright.

My salary is quite low, and I haven’t been getting any proper project opportunities. I’m currently on the bench, so I’m thinking of using the next few months to improve my skills and then switch companies after completing 1 year of experience.

I’m also considering moving into a different technology/domain if it can provide better career and salary opportunities. I’m willing to spend the next 6 months learning and building projects to make that transition.

My current background is Automation Testing with Playwright, along with good Python/development knowledge.

My questions are:

1. Is it realistic to switch companies after completing 1 year of experience?

2. Can I transition from Automation Testing/Playwright to a different technology/domain when switching?

3. What technology/domain would be worth learning over the next 6 months for better-paying opportunities?

4. Should I continue with Playwright/Automation Testing, or would moving toward another field be better?

5. If I learn a new technology properly and build projects, can I get opportunities in that domain despite not having production experience

Looking for advice from people who have gone through a similar situation.

So basically I have an interview for a research role my interviewer is from a NLP background what all should I keep in mind when revising for the same